Beyond the buzzword: the reality of algorithmic empathy in modern marketing

The integration of artificial intelligence (AI) in marketing has introduced the concept of algorithmic empathy, allowing businesses to analyze consumer emotions through advanced clustering techniques and dataset analysis. Using the AI in retail dataset with 656 instances, this study applied the expectation-maximization clustering algorithm to identify patterns in consumer attitudes, particularly dissatisfaction driven by privacy concerns. Real-world examples like Spotify’s success and Facebook’s failures demonstrate the dual-edged nature of AI-driven strategies. Results reveal significant demographic disparities and a gap between consumer expectations and AI performance. This paper emphasizes transparency, tailored marketing strategies, and human oversight to balance personalization and consumer trust, providing actionable recommendations for marketers to implement algorithmic empathy responsibly.